Near the earth's surface, ozone is a highly toxic and reactive pollutant. In order to avoid potentially hazardous concentrations near densely populated areas, accurate forecasts of the temporal variability of ozone are necessary. Several statistical models which may be used to understand the temporal variability of ozone as well as to forecast short-term ozone fluctuations are developed. The models may be divided into two distinct categories: (1) those which forecast daily maximum one-hour average ozone concentrations and (2) those which forecast the diurnal behavior of one-hour average ozone concentrations. To assess the relative utility of each model, their forecast ability is evaluated by statistical comparison with data not used in model development. Most of the developed models appear to perform reasonably well; however, the utility of any forecast model is dependent upon the needs of the user. It is believed that the limits of the "pure time series" method (i.e., mathematical decomposition of time series into various elements) have been approached. Future investigations with these data should attempt to answer specific questions regarding the physical mechanisms governing ozone variability. / Arts, Faculty of / Geography, Department of / Graduate
| Identifer | oai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/26522 |
| Date | January 1987 |
| Creators | Robeson, Scott Michael |
| Publisher | University of British Columbia |
| Source Sets | University of British Columbia |
| Language | English |
| Detected Language | English |
| Type | Text, Thesis/Dissertation |
| Rights | For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
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